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Volumn 6820 LNAI, Issue , 2011, Pages 211-222

Rule protection for indirect discrimination prevention in data mining

Author keywords

Anti discrimination; Data mining; Discrimination prevention; Indirect discrimination; Privacy

Indexed keywords

ANTI-DISCRIMINATION; CLASSIFICATION RULES; DATA SETS; DISCRIMINATION PREVENTION; INDIRECT DISCRIMINATION; INFORMATION SOCIETY; INSURANCE PREMIUMS; LARGE AMOUNTS OF DATA; SENSITIVE ATTRIBUTE; TRAINING DATA SETS;

EID: 79961133426     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22589-5_20     Document Type: Conference Paper
Times cited : (23)

References (12)
  • 6
    • 77958063401 scopus 로고    scopus 로고
    • Three naive Bayes approaches for discrimination-free clas-sification
    • Calders, T., Verwer, S.: Three naive Bayes approaches for discrimination-free clas-sification. Data Mining and Knowledge Discovery 21(2), 277-292 (2010)
    • (2010) Data Mining and Knowledge Discovery , vol.21 , Issue.2 , pp. 277-292
    • Calders, T.1    Verwer, S.2
  • 8


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.